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GENOMIC DIVERSITY GRADIENTS AND FUNCTIONAL DIFFERENTIATION PUT NORTHEAST PACIFIC RIBBON KELP LINEAGES IN THE SPECIATION GREY ZONE

2022· dataset· en· W4394521884 on OpenAlexaboutno aff
Trevor T. Bringloe

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsnot available
Fundersnot available
KeywordsKelpGenetic algorithmEvolutionary biologyDiversity (politics)BiologyRibbonGeographyEcologyAnthropologySociology

Abstract

fetched live from OpenAlex

The transition from reproductively isolated populations to species is not well understood. Genotyping entire genomes holds promise to enhance insights into the process of speciation and the evolutionary relationships among related taxa. Gulf of Alaska ribbon kelp was once recognized as four species before they were folded into Alaria marginata on the basis of DNA barcode markers, though several lineages have continued to be recognized. Here, we used whole genome sequencing datasets to test the hypothesis that these lineages represent incipient species. Whole genomes of 69 individuals from five genetically distinctive lineages in the Gulf of Alaska (USA) and Salish Sea (Canada) were analyzed, along with 63 genomes from three other species of Alaria. Our analysis of >3.4 million Single Nucleotide Polymorphisms reaffirm that organellar and nuclear phylogenetic signals are incongruent in Alaria, producing different topologies among five organellar and six nuclear A. marginata lineages. Lineages also display reproductive isolation, evidenced by a lack of recent admixture across genomes. Genetic distances between A. marginata lineages exceed levels expected of population level divergence, but fall short of distances between species of Alaria. Moreover, we provide evidence of functional genomic differences between the A. marginata lineages, exceeding differences expected between populations, but falling short of larger differences among species. Our results place A. marginata lineages in an evolutionary grey zone, where lineages display substantial differentiation, but not to the level expected of Alaria species. This information shifts taxonomic conversations towards a genome-scale framework that provides a more comprehensive picture of divergence, connectivity, and functional innovation for defining lineages. The datasets presented here pertain to values of exon coverage for the various species of Alaria and lineages of A. marginata. These include gene name/product, uniprot IDs, and GO terms. Tables are for Alaria esculenta populations, Alaria species, and A. marginata lineages.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.027
GPT teacher head0.183
Teacher spread0.155 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreDataset

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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